› TUTORIAL: Combining the Power of High-Throughput Ab Initio Calculations and Machine Learning towards Materials Informatics - Gian-Marco Rignanese, Institute of Condensed Matter and Nanosciences (IMCN), Universite´ Catholique de Louvain
17:00-18:00 (1h)
› A Machine Learning Approach to Predict Tight-binding Parameters for Point Defects via the Projected Density of States - Henry Fried, University of Luxembourg
18:00-18:20 (20min)
› A LINEAR-SCALING APPROACH FOR NONEQUILIBRIUM QUANTUM DYNAMICS - Luis Canonico, ICN2 - Institut Catala de Nanociencia i Nanotecnologia
18:20-18:40 (20min)
› High-dimensional neural network potential for borophene on metallic surfaces - Colin BOUSIGE, Laboratoire des Multimatériaux et Interfaces
18:40-19:00 (20min)